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between quantum computers (via Qiskit) and classical HPC resources Validate the QCS-MiMiC implementation on IBM’s ibm_cleveland quantum computer by reproducing recently published benchmark QM / MM
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of computer simulations to refine the targeted synthesis even more and predict the self-assembly even better. Who we are The Research Training Group RTG2670 – Beyond Amphiphilicity in the second funding phase
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/intercultural communication Experience in processing imaging data is a plus Experience with the named imaging modalities or other optical technologies for plant phenotyping is a plus Equal opportunities and
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civil/electrical/control engineering or mathematics or related study programs with a solid basis in choice modelling and/or reinforcement learning, with knowledge of MATSim is advantageous. Description
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breakage models, e.g. with stochastic tessellations Development and implementation of estimation methods for the model parameters, e.g. with machine learning or statistical methods Lab work and collection
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, remanufacturing, repurposing and recycling to each other for the realization of an agile network. Various machine learning approaches will be used here. Your tasks are: Requirements definition, survey and
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and IT develop innovative radiopharmaceuticals and novel tools for functional characterization, improved imaging and personalized treatment of tumors. The Department of Department Life Science
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, understand its role in therapy resistance, and identify novel regulators using innovative CRISPR screening approaches combined with advanced imaging, single-cell transcriptomics, and phospho-proteomics.
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written and spoken English skills High degree of independence and commitment Experience with machine learning and high-performance computing is advantageous, but not necessary Our Offer: We work on the very
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to submit the dissertation after 3 years and 9 months of research. Desired requirements specific to this project include: experience with a range of relevant computer programming languages such as Python, R